Category: Software Pricing

The Data.com Corporate Hierarchy Viewer displays the Dun & Bradstreet family tree. Users can add any location as an account. The tree also shows sizing variables and SFDC account owners.

Data.com has simplified its pricing from two tiers to a single tier for both its sales intelligence Prospector service and its data hygiene Clean offering. All Prospector users now receive the full Dun & Bradstreet WorldBase record for $150 per seat per month. The full Dun & Bradstreet file was previously priced at $165 per seat per month as part of the Premium offering. Corporate users will see the price rise from $125 to $150 but will receive the following additional content and capabilities due to the product unification:

Corporate family linkages with domestic and global ultimate parents

Corporate family hierarchy viewer

Up to six total SIC/NAICS industry classification codes

Account tradestyle (Doing Business As)

Account delinquency risk (High/Medium/Low)

Account latitude and longitude

Hoover’s First Research call prep content for imported and matched company records

Users are still limited to 300 uploaded or downloaded records per user per month. Additional records are priced at $0.65 per record, unchanged from the previous premium offering. Data.com counts both company and contact records towards the monthly limit. Additional download record credits are not subject to monthly usage limits and may be allocated to Prospector accounts at the Salesforce Administrator’s discretion.

The Clean service price is now $25 per user per month for all users in the instance. All Clean users now receive the full WorldBase file. By standardizing clean to a single edition, Data.com has reduced the price of Clean Premium from $35 to $25.

Simplifying the product bundles makes sense. For premium users, there is a small price cut while there is a price rise for corporate users of Prospector but not Clean. As a premium to Salesforce, having two Data.com editions probably complicated sales discussions unnecessarily.

Lowering the price of Clean also makes sense as higher data quality raises the overall value of the CRM for sales, marketing, and support. Marketing enjoys better segmentation and targeting while sales benefits from improved company intelligence for qualification and fewer misrouted leads. Sales and support also benefit from the better population of contact information (e.g. direct dials, phones) and flags when an individual is no longer affiliated with the account.

While the price reduction makes Prospector more competitive with other Sales Intelligence solutions, Prospector remains at the upper end of the market. For example, InsideView for CRM is priced at $995 per annum, 44% below the price of Data.com Prospector.

Steve Silver, a Research Assistant at Sirius Decisions, recently blogged about a client where the overwhelming reason for losing deals was price. But the client had a differentiated service where price should not have been the primary factor.

Silver discovered the reasons for this anomaly: The field was not used by any departments at the firm. Without an owner, the path of least resistance was selected — the first choice in the picklist. And in the case of the client, 90% of the losses were flagged as price-based.

Did we establish value?

Silver omitted a third reason, and one which is common amongst sales reps. Price is an easy scapegoat for lost opportunities. But if your service is well differentiated and you focus on your value proposition, price should not be the primary loss driver. Yes, some deals will be lost because a competitor low balls the deal (a true price loss), or the prospect simply does not have the financial means to purchase your service (a poorly qualified prospect), but in most cases, losing on price is a failure on the part of sales reps. If they thought about it more, they would realize that price is not an exogenous variable outside of their control. That’s because price is tied to value. Price is the critical variable if your value has not been established.

This isn’t to say that pricing could be wrong. If your competitors are quickly moving up the value curve, your historical price may no longer be sustainable as you become less well differentiated. With good data and analytics, you would capture this shift in the competitive marketplace and act accordingly (e.g. R&D to better differentiate your service, better product bundling, or reduced prices), but price should only dominate the loss reasons in a commodity business.

GIGO

So what else could be gleaned from this situation? First, somebody needs to own data quality within the CRM. If a field is viewed as busywork, your sales reps will populate it with junk data.

Garbage in, Garbage out.

Managers should also be pushing back on reps to better understand why deals were lost so that mistakes can be avoided in the future. Does the sales rep need additional training or coaching? Are additional sales tools needed for competitor handling or establishing value? Are we poorly qualifying opportunities or failing to identify the key decision makers?

Yes, it is easier to move onto the next deal without taking the time to analyze deal losses; but a learning organization needs to understand its failure points.

Sales Operations

Sales Operations should be cross-checking fields. If the loss reason is price or features, then a competitor had a better offering. Was the primary competitor recorded in the CRM? If the competitor is blank, then additional explanation should be required. Did you really lose on price or features if you don’t know who the competitor was?

Or did you lose to no decision or the incumbent because there was insufficient value established to warrant funding the purchase or sustaining the switching costs?

If you don’t collect the data or you allow a field to be treated as busywork, it won’t be available for analysis. I have had several instances where my clients did not record the loss reason or the competitors. I have also had others where the fields were usually blank. In short, the firms were operating in a competitive fog and not using their CRM for market monitoring.

In the end, it is important to not only gather win/loss information, but to use the data for sales training and coaching, marketing communications, sales enablement, and product development. When information is valued by the organization, then sales reps are less likely to blithely skip fields or enter the first field in the required picklist.

Back in July, Fliptop was criticizing its competitors in the predictive analytics space for lack of pricing transparency. Their competitors (Lattice Engines and Mintigo) responded that their products were simply too complex to post prices publicly; Fliptop was a simpler offering targeting the SMB space.

A few weeks later, Fliptop again went on the offensive noting their usability stating “Fliptop has done away with the Wizard of Oz approach to predictive analytics taken by most predictive vendors (‘pay no attention to the man behind the curtain’).”

It was all shaping up to be an interesting case of marketing jujitsu until LinkedIn stepped in and bought Fliptop for its talent.

I mentioned this anecdote because it fit perfectly with a recent study by Robert J Moore of RJMetrics that analyzed pricing transparency in the martech space. Moore found that only forty percent of marketing technology companies post pricing on their website. According to Moore, “companies justify their lack of public pricing based on solution complexity — there are too many factors, they say, that go into a price. These solutions instead offer demos or ‘contact us’ forms.”

Backbone services such as CRM, marketing automation, and ecommerce are most likely to post pricing while middleware services such as data management, tag management, and identity management are the least likely to provide details.

Companies with freemium models are much more likely to provide pricing, but only 16% of the martech firms offered a free baseline service.

Moore found that companies with freemium models are more likely to have a lower paid first tier than companies that eschew freemium pricing. Non-freemium vendors generally have their lowest tier pricing 2X to 5X that of freemium vendors. Freemium vendors averaged $100 per month for their lowest tier while non-freemium vendors were slightly above $250 per month.

If you’re a vendor and want to quote pricing publicly, the data is clear: most of your competitors are quoting in monthly terms. And they’re probably doing it for a reason.
– Robert J Moore of RJ Metrics

Moore also found that monthly pricing dominates with fewer than 15% of companies advertising annual or one-time prices. The dominance of monthly pricing held across all five martech sectors. As Moore noted, this pricing is for vendors with transparent pricing; annual pricing is much more likely to be quoted by non-pricing transparent vendors when assembling a detailed quote.

The study was based upon the 1,876 company Marketing Technology Landscape put together by Scott Brinker. RJMetrics employed Amazon’s Mechanical Turk to collect the data.